Initial Audit Task Execution

Simulate an initial audit by providing the agent with a document excerpt and a specific policy area (e.g., 'Data Privacy'). The agent should:
1. Use the `policy_retriever` tool to find relevant policy documents.
2. Analyze the document excerpt in the context of retrieved policies.
3. Identify any potential violations or risks.
4. Use the `mem0_saver` tool to store a summary of its initial findings for future reference.

```python
# ... (previous agent setup code)

thread = client.beta.threads.create()

message = client.beta.threads.messages.create(
    thread_id=thread.id,
    role="user",
    content="Please audit the following document excerpt for Data Privacy policy compliance: 'Our internal analytics system collects IP addresses without notifying users, storing them indefinitely.'"
)

run = client.beta.threads.runs.create(
    thread_id=thread.id,
    assistant_id=assistant.id
)

# Polling mechanism to check run status and handle tool calls
while run.status in ['queued', 'in_progress', 'requires_action']:
    if run.status == 'requires_action':
        print('Agent requires action (tool call)...')
        tool_outputs = []
        for tool_call in run.required_action.submit_tool_outputs.tool_calls:
            if tool_call.function.name == 'policy_retriever':
                args = eval(tool_call.function.arguments)
                output = policy_retriever(args['query'])
                tool_outputs.append({
                    "tool_call_id": tool_call.id,
                    "output": str(output)
                })
            elif tool_call.function.name == 'mem0_saver':
                args = eval(tool_call.function.arguments)
                output = mem0_saver(args['key'], args['value'])
                tool_outputs.append({
                    "tool_call_id": tool_call.id,
                    "output": str(output)
                })
        if tool_outputs:
            run = client.beta.threads.runs.submit_tool_outputs(
                thread_id=thread.id,
                run_id=run.id,
                tool_outputs=tool_outputs
            )
        else:
            # Handle cases where no tool outputs are generated but action is required
            break

    run = client.beta.threads.runs.retrieve(thread_id=thread.id, run_id=run.id)
    # time.sleep(1) # Add a small delay if polling frequently

if run.status == 'completed':
    messages = client.beta.threads.messages.list(thread_id=thread.id)
    for msg in messages.data:
        if msg.role == 'assistant':
            print(f"Agent: {msg.content[0].text.value}")

```